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Encoder-free Speech-LLM通过元数据监督预训练提升说话人辨识与副语言理解
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2026-10-02,arXiv Audio and Speech 频道发布一手论文,提出 metadata-supervised pretraining(MSP)方法,用于无编码器 Speech-LLM 的训练。该方法利用说话人身份、情感等语音元数据进行监督预训练,并引入 speaker-aware utterance composition(SAUC)与随机跨度掩码正则化,以提升模型在说话人辨识与副语言理解方面的能力。
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Oct 2, 2026
- arXiv · Audio and Speech教大语言模型识别说话人:Metadata-Supervised Pretraining 用于无编码器语音-LLM
论文提出 metadata-supervised pretraining(MSP),利用说话人身份和情感等语音属性训练无编码器 Speech-LLM,并引入 speaker-aware utterance composition(SAUC)和随机跨度掩码正则化。
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